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Open nowPosted 269 days ago

模型部署优化实习生

agirobot/internrecruitment367 open roles

Where
Shanghai, Chinese Mainland
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Your applicationOpen now模型部署优化实习生agirobot/internrecruitment · Shanghai, Chinese Mainland

  1. YouYes, apply to this one.

  2. CV RocketCV written for this posting.

  3. 25 readersRecruiter, hiring manager, skeptic. Round after round.

  4. CV RocketApplied on agirobot/internrecruitment's own form.

The reply lands in your private mailbox

3×more interviews than doing it yourself with ChatGPT.

The clock on this job

Early applications get read.

12.1% of postings close within 7 days. Measured by our own scanner across the market. agirobot/internrecruitment postings stay open a median of 2 days.

Share of postings closed within
  1. 2.1%1 day
  2. 4.5%3 days
  3. 12.1%7 days
  4. 19.1%14 days
  5. 35.6%30 days
  6. 52.7%60 days
This job: posted 269 days ago

agirobot/internrecruitment median: 2 days open

The posting

1. 参与 PC、端侧 AI 应用原型开发与验证，覆盖数据采集、标注、预处理、模型选型适配、分布式训练加速、训练策略调优、推理链路性能调优全流程； 2. 负责 PC 平台、Jetson 系列开发板（Nano、Orin、Thor 等）的模型训练、工程部署、训练与推理性能优化； 3. 开展大模型 / 视觉模型分布式训练实践，基于 DDP、FSDP、DeepSpeed、ZeRO 优化策略完成多卡训练提速、显存优化；运用混合精度、梯度检查点、梯度累积等技术降低显存开销，支持 LoRA/QLoRA 轻量化微调； 4. 开展训练链路瓶颈分析，利用 PyTorch Profiler、Nsight 等工具定位计算、通信、数据 IO 瓶颈，优化数据加载管线，提升训练吞吐与稳定性； 5. 落地模型压缩方案：量化、剪枝、知识蒸馏；依托 ONNX、TensorRT、TRT-LLM 完成模型转换、编译与端侧推理加速； 6. 参与 VLA 视觉语言动作模型、大语言模型部署落地，使用 CUDA、vLLM、llama.cpp 开展推理瓶颈定位与性能调优； 7. 持续优化训练收敛效果、推理延迟、显存占用，开展对比实验与方案验证； 8. 撰写技术文档：部署手册、性能测试报告、训练 / 推理优化方案、技术总结； 9. 定位解决训练、推理阶段各类软硬件问题，配合团队推进项目落地，完成其他 AI 模型开发相关任务。

1. 在读本科及以上学历，计算机科学与技术、人工智能、电子信息、自动化等相关专业； 2. 扎实 Python 基础，具备 C/C++ 开发能力，熟练使用 Ubuntu Linux 开发环境； 3. 掌握深度学习基础理论，熟练使用 PyTorch 框架； 4. 了解分布式训练相关技术，包括 DDP、FSDP、DeepSpeed、ZeRO 优化、混合精度训练、梯度检查点、LoRA/QLoRA 微调等；能够使用 Profiler、Nsight 等工具剖析训练性能瓶颈，了解 NCCL 通信优化、多机多卡训练者优先； 5. 了解模型压缩技术：量化、剪枝、知识蒸馏；熟悉 ONNX、TensorRT 模型转换与推理优化工具； 6. 拥有 Jetson 端侧模型部署、性能调优实战经验优先； 7. 了解 VLA 视觉语言动作模型，掌握基础 CUDA 编程，接触过 vLLM、TRT-LLM、llama.cpp 大模型推理框架优先； 8. 具备较强问题排查、自主学习能力，良好的沟通与团队协作意识，工作主动负责； 9. 每周至少实习 4 天，可连续实习 3 个月及以上优先。 10. 以上提到的技术会一部分即可。

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